Covid-19 vaccine acceptance, hesitancy, and refusal among Canadian healthcare workers: A multicenter survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Determinants of COVID-19 vaccine acceptance among healthcare workers (HCW) remains poorly understood. We assessed HCWs' willingness to be vaccinated and reasons underlying hesitancy. METHODS: Cross-sectional survey across 17 healthcare institutions. HCWs eligible for vaccination (Pfizer-BioNTech mRNA) in December 2020 were invited to receive immunization. Multivariate logistic regression was performed to identify predictors of acceptance. Reasons for refusal among those who never intended to be vaccinated (ie, firm refusers) and those who preferred delaying vaccination (ie, vaccine hesitants) were assessed. RESULTS: Among 2,761 respondents (72% female, average age, 44), 2,233 (80.9%) accepted the vaccine. Physicians, environmental services workers and healthcare managers were more likely to accept vaccination compared to nurses. Male sex, age over 50, rehabilitation center workers, and occupational COVID-19 exposure were independently associated with vaccine acceptance by multivariate analysis. Factors for refusal included vaccine novelty, wanting others to receive it first, and insufficient time for decision-making. Among those who declined, 74% reported they may accept future vaccination. Vaccine firm refusers were more likely than vaccine hesitants to distrust pharmaceutical companies and to prefer developing a natural immunity by getting COVID-19. CONCLUSIONS: Vaccine hesitancy exists among HCWs. Our findings provide useful information to plan future interventions and improve acceptance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it